68 lines
1.9 KiB
Plaintext
68 lines
1.9 KiB
Plaintext
---
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title: Databricks
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hide_title: true
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sidebar_position: 37
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version: 1
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---
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## Databricks
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To connect to Databricks, first install [databricks-dbapi](https://pypi.org/project/databricks-dbapi/) with the optional SQLAlchemy dependencies:
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```bash
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pip install databricks-dbapi[sqlalchemy]
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```
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There are two ways to connect to Databricks: using a Hive connector or an ODBC connector. Both ways work similarly, but only ODBC can be used to connect to [SQL endpoints](https://docs.databricks.com/sql/admin/sql-endpoints.html).
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### Hive
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To use the Hive connector you need the following information from your cluster:
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- Server hostname
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- Port
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- HTTP path
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These can be found under "Configuration" -> "Advanced Options" -> "JDBC/ODBC".
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You also need an access token from "Settings" -> "User Settings" -> "Access Tokens".
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Once you have all this information, add a database of type "Databricks (Hive)" in Superset, and use the following SQLAlchemy URI:
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```
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databricks+pyhive://token:{access token}@{server hostname}:{port}/{database name}
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```
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You also need to add the following configuration to "Other" -> "Engine Parameters", with your HTTP path:
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```
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{"connect_args": {"http_path": "sql/protocolv1/o/****"}}
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```
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### ODBC
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For ODBC you first need to install the [ODBC drivers for your platform](https://databricks.com/spark/odbc-drivers-download).
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For a regular connection use this as the SQLAlchemy URI:
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```
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databricks+pyodbc://token:{access token}@{server hostname}:{port}/{database name}
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```
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And for the connection arguments:
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```
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{"connect_args": {"http_path": "sql/protocolv1/o/****", "driver_path": "/path/to/odbc/driver"}}
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```
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The driver path should be:
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- `/Library/simba/spark/lib/libsparkodbc_sbu.dylib` (Mac OS)
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- `/opt/simba/spark/lib/64/libsparkodbc_sb64.so` (Linux)
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For a connection to a SQL endpoint you need to use the HTTP path from the endpoint:
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```
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{"connect_args": {"http_path": "/sql/1.0/endpoints/****", "driver_path": "/path/to/odbc/driver"}}
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```
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